Prof. Dr. Lucy Pao 

University of Colorado Boulder, USA
May 2025 - Aug 2025
Fellow
Jun 2023 - Dec 2023
Fellow
Jun 2019 - Aug 2019
Fellow
Oct 2016 - Jul 2017
Fellow

Lucy Pao

Projects & Publications

Abstract

To combat climate change, many countries are decarbonizing their electric power grids by significantly increasing power generated from wind, solar, and other renewable energy sources. To further decrease the cost of wind energy in order to accelerate the deployment of wind farms, wind turbines are being designed at ever larger scales, which is challenging due to greater structural loads and deflections. Large-scale systems such as modern wind turbines increasingly require a control co-design approach, where the system design and control design are performed in a more integrated fashion. I propose to investigate the control co-design of extreme-scale wind turbines (with blade lengths greater than 150 meters), floating wind turbines, and wind farms. With 80% of offshore wind resources over waters deeper than 60 meters, floating wind turbines are needed to harness this vast energy source offshore, as it becomes cost prohibitive to install fixed-bottom wind turbines in such deep waters. With floating wind farms, there are additional degrees of freedom such as being able to move each floating turbine to continuously optimize the wind farm layout as wind speeds and directions change. Hence, there are opportunities to reduce the cost of floating wind energy to be competitive with fixed-bottom offshore wind energy. Both conceptual and simulation studies as well as experimental campaigns will be pursued collaboratively with fellows at HWK and colleagues at nearby institutions.

Cooperation partner
Prof. Dr. Martin Kühn, ForWind - Zentrum für Windenergieforschung
Prof. Dr.-Ing. Andreas Rauh, Carl von Ossietzky Universität Oldenburg
Publications
Pao, L., Abbas, N. J., Bortolloti, P., Kelley, C., Paquette, J., and Johnson, N. (2023). Aero-Servo-Elastic Co-Optimization of Large Wind Turbine Blades with Distributed Aerodynamic Control Devices. Wind Energy Science, 8, 26. https://doi.org/10.1002/we.2840
Pao, L., Veers, P., Bottasso, C., Manuel, L., Naughton, J., Paquette, J., Robertson, A., Robinson M., Ananthan, S., Barlas, A. Bianchini, A., Bredmose, H., González Horcas, S., Keller, J., Madsen, H. A., Manwell, J., Moriarty, P., Nolet, S., and Rinker, J. (2023). Grand Challenges in the Design, Manufacture, and Operation of Future Wind Turbine Systems. Wind Energy Science, 7, 8. https://doi.org/10.5194/wes-8-1071-2023
Pao, L., Kaminski, M., Simpson, J., Loth, E., Fingersh, L. J., Scholbrock, A., Johnson, N., Johnson, K., and Griffith, D. T. (). Gravo-Aeroelastically-Scaled Demonstrator Field Tests to Represent Blade Response of a Flexible Extreme-Scale Downwind Turbine. Renewable Energy, 218. https://doi.org/10.1016/j.renene.2023.119217
Pao, L., Florence, IT., Pusch, M., Phadnis, M., Jeong, M., Qin, C., and Loth, E. (2024). Impact of Blade Pitch Actuation System on Wind Turbine Cost and Energy Production. J. Physics: Conf. Series: Proc. Science of Making Torque from Wind, Florence, IT.
Pao, L., Henry, A., Sinner, M., and King, J. (2023). Online Learning of Effective Turbine Wind Speed in Wind Farms. Proc. IEEE Conf. on Decision and Control, Singapore, 1569-1574. https://doi.org/10.1109/cdc49753.2023.10383909
Pao, L., Pusch, M., Stockhouse, D., Abbas, N., and Phadnis, M. (2024). Optimal Operating Points for Wind Turbine Control and Co-Design. Wind Energy. https://doi.org/10.1002/we.2879
Pao, L., Stockhouse, D., Pusch, M., Damiani, R., and Sirnivas, S. (2024). Robust Multi-Loop Control of a Floating Wind Turbine. Wind Energy. https://doi.org/10.1002/we.2864
Pao, L. Y., Pusch, M., and Zalkind, D. S. (). Control Co-Design of Wind Turbines. Annual Review of Control, Robotics, and Autonomous Systems, 7: 7.1-7.26. https://doi.org/org/10.1146/annurev-control-061423-101708
Pao, L., Abbas, N. J., Jasa, J., Zalkind, D. S., and Wright, A. (2024). (2024), Control Co-design of a Floating Offshore Wind Turbine,. Applied Energy, Part B, 353. https://doi.org/10.1016/j.apenergy.2023.122036
Pao, L., Phadnis, M., and Zalkind, D. (2024). Advanced Wind Turbine Control Development Using Field Test Analysis for Generator Overspeed Mitigation,. Wind Energy. https://doi.org/10.1002/we.2860
Pao, L., Escalera Mendoza, A. S., Griffith, D. T., Jeong, M., Qin, C., Loth, E., Phadnis, M., and Selig, M. S. (2023) (2023). Aero-Structural Rapid Screening of New Design Concepts for Offshore Wind Turbines. Renewable Energy, Part 2, 219. https://doi.org/10.1016/j.renene.2023.119519
Pao, L., Stockhouse, D., Zalkind, D., and Ross, H. (2024). Analysis of Power-Maximizing Region-2 Controllers for Wind and Marine Turbines. J. Physics: Conf. Series: Proc. Science of Making Torque from Wind, Florence, IT.
Pao, L., Khargonekar, P., Samad, T., Amin, S., Chakrabortty, A., Dabbene, F., Das, A., Fujita, M., Garcia-Sanz, M., Gayme, D., Ilić, M., Mareels, I., Moore, K., Rajhans, A., Stoustrup, J., Zafar, J., and Bauer, M. (2024). Climate Change Mitigation, Adaptation, and Resilience: Challenges and Opportunities for the Control Systems Community. IEEE Control Systems Magazine.
Pao, L., Phadnis, M., Escalera Mendoza, A. S., Jeong, M., Loth, E., Griffith, D. T., and Pusch, M. (2024). Comparison of 25 MW Downwind and Upwind Turbine Designs with Individual Pitch Control. J. Physics: Conf. Series: Proc. Science of Making Torque from Wind.
Cooperation partner
Prof. Dr. Martin Kühn, ForWind - Zentrum für Windenergieforschung
Prof. Dr.-Ing. Andreas Rauh, Carl von Ossietzky Universität Oldenburg
Publications
P. Veers, K. Dykes, E. Lantz, S. Barth, C. Bottasso, O. Carlson, A . Clifton, J. Green, P. Green, H. Holttinen, D. Laird, V. Lehtomäki, J. K. Lundquist, J. Manwell, M. Marquis, C. Meneveau, P. Moriarty, X. Munduate, M. Muskulus, J. Naughton, L. Pao, J. Paquette, J. Peinke, A. Robertson, J. S. Rodrigo, A. M. Sempreviva, J. C. Smith, A. Tuohy, and R. Wiser (2019). Grand Challenges in the Science of Wind Energy. Science, 6464, 366. https://doi.org/10.1126/science.aau2027
Braker, R. A., Luo, Y., Pao, L.Y., and Andersson, S.B. (2020). Improving the Image Acquisition Rate of an Atomic Force Microscope through Sub-sampling and Reconstruction. IEEE/ASME Transactions on Mechatronics, 2, 25, 570-580.
Mehdi, V., Petrović, V., Pao, L.Y., and Kühn, M. (2021). Model Predictive Active Power Control for Optimal Structural Load Equalization in Waked Wind Farms. IEEE Transactions on Control Systems Technology, 1-15.
Zalkind, D. S., Ananda, G.K., Chetan, M., Martin, D.P., Bay, C.J., Johnson, K.E., Loth, E., Todd Griffith, D., Selig, M.S., and Pao, L.Y. (2019). System-Level Design Studies for Large Rotors. Wind Energy Science, 4, 595-618. https://doi.org/10.5194/wes-4-595-2019
Chao, (Chris) Q., Lotha, E., Zalkind, D. S., Pao, L. Y., Yao, S.,Todd Griffith, D., Selig, M.S., Damiani, R. (2020). Downwind coning concept rotor for a 25 MW offshore wind turbine. Renewable Energy, 156, 314-327.
Pao, L.Y., Zalkind, D.S., Todd Griffith, D., Chetan, M., Selig, M.S., Ananda, G.K., Bayd, C.J., Stehly, T., and Lothe, E. (2021). Control co-design of 13 MW downwind two-bladed rotors to achieve 25% reduction in levelized cost of wind energy. Annual Reviews in Control. https://doi.org/10.1016/j.arcontrol.2021.02.001
Pao, L. Y. (2020). Active Power Control of Wind Power Plants for Grid Integration. J. Baillieul and T. Samad, Encyclopedia of Systems and Control. https://doi.org/10.1007/978-1-4471-5102-9_272-2
Braker, R. A., and Pao, L. Y. (2017). An Application of the Fast Gradient Method to Model Predictive Control of an Atomic Force Microscope X-Y Stage. Proc. IEEE Conf. Control Technology and Applications, 111-116.
Zalkind, D.S., Dall’Anese, E., Pao, L.Y., et. al. (2020). Automatic controller tuning using a zeroth-order optimization algorithm. Wind Energy Science, 4, 5, 1579-1600.
Pao, L., Zalkind, D., Griffith, D., Chetan, M., Selig, M., Ananda, G., Bay, C., Stehly, T., Loth, E. (2021). Control co-design of 13 MW downwind two-bladed rotors to achieve 25% reduction in levelized cost of wind energy. Annual Reviews in Control, Elsevier, 51, 331-343.
Ungurán, R., Petrović, V., Pao, L., and Kühn, M. (2019). Uncertainties Identification of Blade- Mounted Lidar-Based Inflow Wind Speed Measurements for Robust Feedback-Feedforward Control Synthesis. Wind Energy Science, 4, 677-692. https://doi.org/10.5194/wes-4-677-2019